780 resultados para insulin, therapeutic use


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Loss of appetite and ensuing weight loss is a key feature of severe illnesses. Protein-energy malnutrition (PEM) contributes significantly to the adverse outcome of these conditions. Pharmacological interventions to target appetite stimulation have little efficacy but considerable side effects. Therefore nutritional therapy appears to be the logical step to combat inadequate nutrition. However, clinical trial data demonstrating benefits are sparse and there is no current established standard algorithm for use of nutritional support in malnourished, acutely ill medical inpatients. Recent high-quality evidence from critical care demonstrating harmful effects when parenteral nutritional support is used indiscriminately has led to speculation that loss of appetite in the acute phase of illness is indeed an adaptive, protective response that improves cell recycling (autophagy) and detoxification. Outside critical care, there is an important gap in high quality clinical trial data shedding further light on these important issues. The selection, timing, and doses of nutrition should be evaluated as carefully as with any other therapeutic intervention, with the aim of maximising efficacy and minimising adverse effects and costs. In light of the current controversy, a reappraisal of how nutritional support should be used in acutely ill medical inpatients outside critical care is urgently required. The aim of this review is to discuss current pathophysiological concepts of PEM and to review the current evidence for the efficacy of nutritional support regarding patient outcomes when used in an acutely ill medical patient population outside critical care.

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Treatment options for patients with schizophrenia demand further improvement. One way to achieve this improvement is the translation of findings from basic research into new specific interventions. Beyond that, addressing the therapy relationship has the potential to enhance both pharmacological and non-pharmacological treatments. This paper introduces motive-oriented therapeutic relationship (MOTR) building for schizophrenia. MOTR enables therapists to proactively adapt to their patient’s needs and to prevent problematic behaviors. For example, a patient might consider medication as helpful in principle, but the rejection of medication might be one of his few remaining means for his acceptable motive to stay autonomous despite hospitalization. A therapist who is motiveoriented proactively offers many degrees of freedom to this patient in order to satisfy his need for autonomy and to weaken the motivational basis for not taking medication. MOTR makes use of findings from basic and psychotherapy research and is generic in this respect, but at the same time guides therapeutic action precisely and flexibly in a patient oriented way.

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INTRODUCTION Daylight-mediated photodynamic therapy has been shown to be an effective therapy for actinic keratoses (AKs) and a simple and tolerable treatment procedure in three randomized Scandinavian studies and two recent Phase III randomized controlled studies in Australia and Europe. OBJECTIVES To establish consensus recommendations for the use of daylight photodynamic therapy (DL-PDT) using topical methyl aminolaevulinate (MAL) in European patients with AKs. METHODS The DL-PDT consensus recommendations were developed on behalf of the European Society for Photodynamic Therapy in Dermatology and comprised of 10 dermatologists from different European countries with experience in how to treat AK patients with PDT. Consensus was developed based on literature review and experience of the experts in the treatment of AK using DL-PDT. RESULTS The recommendations arising from this panel of experts provide general guidance on the use of DL-PDT as a dermatological procedure with specific guidance regarding patient selection, therapeutic indications, when to treat, pre-treatment skin preparation, MAL application and daylight exposure for patients with AK in different countries of Europe. CONCLUSIONS This consensus recommendation provides a framework for physicians to perform DL-PDT with MAL cream while ensuring efficiency and safety in the treatment of patients with AK in different European countries.

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BACKGROUND Prior epidemiologic studies suggest inverse relations between diabetes and glioma risk, but the underlying mechanisms, including use of antidiabetic drugs, are unknown. METHODS We therefore performed a matched case-control analysis using the Clinical Practice Research Datalink (CPRD). We identified incident glioma cases diagnosed between 1995 and 2012 and matched each case with 10 controls on age, gender, calendar time, general practice, and years of active history in the CPRD. We performed conditional logistic regression to estimate odds ratios (ORs) with 95% CIs, adjusted for body mass index and smoking. RESULTS We identified 2005 cases and 20 050 controls. Diabetes was associated with decreased risk of glioma (OR = 0.74; 95% CI = 0.60-0.93), particularly glioblastoma (OR = 0.69; 95% CI = 0.51-0.94). Glioblastoma risk reduction was markedly pronounced among diabetic men (OR = 0.60; 95% CI = 0.40-0.90), most apparently for those with diabetes of long-term duration (OR for >5 vs 0 y = 0.46; 95% CI = 0.26-0.82) or poor glycemic control (OR for HbA1c ≥8 vs <6.5% = 0.20; 95% CI = 0.06-0.70). In contrast, the effect of diabetes on glioblastoma risk was absent among women (OR = 0.85; 95% CI = 0.53-1.36). No significant associations with glioma were found for use of metformin (OR for ≥30 vs 0 prescriptions = 0.72; 95% CI = 0.38-1.39), sulfonylureas (OR = 0.71; 95% CI = 0.39-1.30), or insulin (OR = 0.79; 95% CI = 0.37-1.69). CONCLUSIONS Antidiabetic treatment appears to be unrelated to glioma, but long-term diabetes duration and increased HbA1c both show decreased glioma risk. Stronger findings in men than women suggest low androgen levels concurrent with diabetes as a biologic mechanism.

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Increasing attention has been given to the connection between metabolism and cancer. Under aerobic conditions, normal cells predominantly use oxidative phosphorylation for ATP generation. In contrast, increase of glycolytic activity has been observed in various tumor cells, which is known as Warburg effect. Cancer cells, compared to normal cells, produce high levels of Reactive Oxygen Species (ROS) and hence are constantly under oxidative stress. Increase of oxidative stress and glycolytic activity in cancer cells represent major biochemical alterations associated with malignant transformation. Despite prevalent upregulation of ROS production and glycolytic activity observed in various cancer cells, underlying mechanisms still remain to be defined. Oncogenic signals including Ras has been linked to regulation of energy metabolism and ROS production. Current study was initiated to investigate the mechanism by which Ras oncogenic signal regulates cellular metabolism and redox status. A doxycycline inducible gene expression system with oncogenic K-ras transfection was constructed to assess the role played by Ras activation in any given studied parameters. Data obtained here reveals that K-ras activation directly caused mitochondrial dysfunction and ROS generation, which appeared to be mechanistically associated with translocation of K-ras to mitochondria and the opening of the mitochondrial permeability transition pore. K-ras induced mitochondrial dysfunction led to upregulation of glycolysis and constitutive activation of ROS-generating NAD(P)H Oxidase (NOX). Increased oxidative stress, upregulation of glycolytic activity, and constitutive activated NOX were also observed in the pancreatic K-ras transformed cancer cells compared to their normal counterparts. Compared to non-transformed cells, the pancreatic K-ras transformed cancer cells with activated NOX exhibited higher sensitivity to capsaicin, a natural compound that appeared to target NOX and cause preferential accumulation of oxidative stress in K-ras transformed cells. Taken together, these findings shed new light on the role played by Ras in the road to cancer in the context of oxidative stress and metabolic alteration. The mechanistic relationship between K-ras oncogenic signals and metabolic alteration in cancer will help to identify potential molecular targets such as NAD(P)H Oxidase and glycolytic pathway for therapeutic intervention of cancer development. ^

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Imatinib mesylate, a selective inhibitor of KIT, PDGFR, and Abl kinases, has shown significant success as a therapy for patients with advanced gastrointestinal stromal tumors (GISTs). However, the underlying mechanisms of imatinib-induced cytotoxicity are not well understood. Using gene expression profiling and real-time PCR for target validation, we identified insulin-like growth factor binding protein-3 (IGFBP3) to be to be up-regulated after imatinib treatment in imatinib-sensitive GISTs. IGFBP3 is a multifunctional protein that regulates cell proliferation and survival and mediates the effects of a variety of anti-cancer agents through IGF-dependent and IGF-independent mechanisms. Therefore, we hypothesized that IGFBP3 mediates GIST cell response to imatinib. To test this hypothesis, we manipulated IGFBP3 protein levels in two KIT mutant, imatinib-sensitive GIST cell lines and assessed the resultant changes in cell viability, survival, and imatinib sensitivity. In GIST882 cells, endogenous IGFBP3 was required for cell viability. However, inhibiting imatinib-induced IGFBP3 up-regulation by RNA interference or neutralization resulted in reduced drug sensitivity, suggesting that IGFBP3 sensitizes GIST882 cells to imatinib. GIST-T1 cells, on the other hand, had no detectable levels of endogenous IGFBP3, nor did imatinib induce IGFBP3 up-regulation, in contrast to our previous findings. IGFBP3 overexpression in GIST-T1 cells reduced viability but did not induce cell death; rather, the cells became polyploid through a mechanism that may involve attenuated Cdc20 expression and securin degradation. Moreover, IGFBP3 overexpression resulted in a loss of KIT activation and decreased levels of mature KIT. Consistent with this, GIST-T1 cells overexpressing IGFBP3 were less sensitive to imatinib. Furthermore, as neither GIST882 cells nor GIST-T1 cells expressed detectable levels of IGF-1R, IGFBP3 is likely not exerting its effects by modulating IGF signaling through IGF-1R or IR/IGF-1R hybrid receptors in these cell lines. Collectively, these findings demonstrate that IGFBP3 has cell-dependent effects and would, therefore, not be an ideal marker for identifying imatinib response in GISTs. Nevertheless, our results provide preliminary evidence that IGFBP3 may have some therapeutic benefits in GISTs. ^

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Can the early identification of the species of staphylococcus responsible for infection by the use of Real Time PCR technology influence the approach to the treatment of these infections? ^ This study was a retrospective cohort study in which two groups of patients were compared. The first group, ‘Physician Aware’ consisted of patients in whom physicians were informed of specific staphylococcal species and antibiotic sensitivity (using RT-PCR) at the time of notification of the gram stain. The second group, ‘Physician Unaware’ consisted of patients in whom treating physicians received the same information 24–72 hours later as a result of blood culture and antibiotic sensitivity determination. ^ The approach to treatment was compared between ‘Physician Aware’ and ‘Physician Unaware’ groups for three different microbiological diagnoses—namely MRSA, MSSA and no-SA (or coagulase negative Staphylococcus). ^ For a diagnosis of MRSA, the mean time interval to the initiation of Vancomycin therapy was 1.08 hours in the ‘Physician Aware’ group as compared to 5.84 hours in the ‘Physician Unaware’ group (p=0.34). ^ For a diagnosis of MSSA, the mean time interval to the initiation of specific anti-MSSA therapy with Nafcillin was 5.18 hours in the ‘Physician Aware’ group as compared to 49.8 hours in the ‘Physician Unaware’ group (p=0.007). Also, for the same diagnosis, the mean duration of empiric therapy in the ‘Physician Aware’ group was 19.68 hours as compared to 80.75 hours in the ‘Physician Unaware’ group (p=0.003) ^ For a diagnosis of no-SA or coagulase negative staphylococcus, the mean duration of empiric therapy was 35.65 hours in the ‘Physician Aware’ group as compared to 44.38 hours in the ‘Physician Unaware’ group (p=0.07). However, when treatment was considered a categorical variable and after exclusion of all cases where anti-MRS therapy was used for unrelated conditions, only 20 of 72 cases in the ‘Physician Aware’ group received treatment as compared to 48 of 106 cases in the ‘Physician Unaware’ group. ^ Conclusions. Earlier diagnosis of MRSA may not alter final treatment outcomes. However, earlier identification may lead to the earlier institution of measures to limit the spread of infection. The early diagnosis of MSSA infection, does lead to treatment with specific antibiotic therapy at an earlier stage of treatment. Also, the duration of empiric therapy is greatly reduced by early diagnosis. The early diagnosis of coagulase negative staphylococcal infection leads to a lower rate of unnecessary treatment for these infections as they are commonly considered contaminants. ^

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Background: Pancreatic cancer is the fourth most common cause of cancer death in the United States. Despite advances in cancer treatment, prognosis of pancreatic cancer remains extremely poor with survival rates of 24% and 5% in 1 and 5 years, respectively. Many patients with pancreatic cancer have a history of diabetes and are treated with various antidiabetic regimens including metformin. In multiple retrospective studies, metformin has been associated with decreased risk of cancer and cancer-related mortality. Metformin has also been reported to inhibit the growth of cancer cells, both in vitro and in vivo.^ Methods: We conducted a retrospective cohort study to examine the survival benefit of metformin in diabetic patients with pancreatic cancer at MD Anderson Cancer Center (MDACC). A dataset of 397 patients who carried the diagnosis of "Diabetes Mellitus" and "Pancreatic Cancer" at MD Anderson were screened for this study. ^ Results: Mean age of patients at diagnosis of cancer was 64.0 ± 8.7 years (range 37-84). The majority of the patients were male (65.6%) and of Caucasian race (78.5%). The most common antidiabetic regimen used were insulin and metformin (in 39.1% and 38.7%, respectively). Patients' cancer were staged as resectable in 34.1%, locally advanced unresectable in 29.1%, and disseminated disease in 36.7% of cases. Overall 1-year and 3-year survival rates for all stages combined were 51.8% and 7.6%, respectively. Earlier stage, metformin use, low CA19-9 level, better ECOG performance status, surgical intervention, negative surgical margins, and smaller tumor size were associated with longer survival. Metformin use was associated with a 33% decrease in risk of death (HR: 0.67; 95% CI: 0.51-0.88). Multivariate Cox proportional hazard regression showed hazard ratio of 1.77 (95% CI 1.49-2.10) for cancer stage, 0.65 (95% CI 0.49-0.86) for metformin use, and 1.68 (95% CI 1.26-2.23) for CA 19-9 level above population median. ^ Conclusion: Our study suggests that metformin may improve the outcome in diabetic patients with pancreatic cancer independently of other known prognostic factors. Pancreatic cancer carries extremely poor prognosis; metformin may provide a suitable adjunct therapeutic option for pancreatic cancer in patients with and without diabetes mellitus.^

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Over 1.2 million Americans are currently living with a traumatic spinal cord injury (SCI). Despite the need for effective therapies, there are currently no proven effective treatments that can improve recovery of function in SCI patients. Many therapeutic compounds have shown promise in preclinical models of SCI, but all of these have fallen short in clinical trials. P-glycoprotein (Pgp) is an active transporter expressed on capillary endothelial cell membranes at the blood-spinal cord barrier (BSCB). Pgp limits passive diffusion of blood-borne drugs into the CNS, by actively extruding drugs from the endothelial cell membrane. Pgp can become pathologically up-regulated, thus greatly impeding therapeutic drug delivery (‘multidrug resistance’). Importantly, many drugs that have been evaluated for the treatment of SCI are Pgp substrates. We hypothesized that Pgp-mediated drug resistance diminishes the delivery and efficacy of neuroprotective drugs following SCI. We observed a progressive, spatial spread of Pgp overexpression within the injured spinal cord. To assess Pgp function, we examined spinal cord uptake of systemically-delivered riluzole, a drug that is currently being evaluated in clinical trials as an SCI intervention. Blood-to-spinal cord riluzole penetration was reduced following SCI in wild-type but not Pgp-null rats, highlighting a critical role for Pgp in mediating spinal cord drug resistance after injury. Others have shown that pro-inflammatory signaling drives Pgp up-regulation in cancer and epilepsy. We have detected inflammation in both acutely- and chronically-injured spinal cord tissue. We therefore evaluated the ability of the dual COX-/5-LOX inhibitor licofelone to attenuate Pgp-mediated drug resistance following SCI. Licofelone treatment both reduced spinal cord Pgp levels and enhanced spinal cord riluzole bioavailability following SCI. Thus, we propose that licofelone may offer a new combinatorial treatment strategy to enhance spinal cord drug delivery following SCI. Additionally, we assessed the ability of licofelone, riluzole, or both to enhance recovery of locomotor function following SCI. We found that licofelone treatment conferred a significant improvement in hindlimb function that was sustained through the end of the study. In contrast, riluzole did not improve functional outcome. We therefore conclude that licofelone holds promise as a potential neuroprotective intervention for SCI.

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Brain metastasis is a common cause of mortality in cancer patients. Approximately 20-30% of breast cancer patients acquire brain metastasis, yet potential therapeutic targets remain largely unknown. The type I insulin-like growth factor receptor (IGF- IR) is known to play a role in the progression of breast cancer and is currently being investigated in the clinical setting for various types of cancer. The present study demonstrates that the IGF-IR signaling axis is constitutively active in brain-seeking sublines of breast cancer cells, driving an increase in in vitro metastatic properties. We demonstrate that IGF-IR signaling is activated in an autocrine manner as a result of IGFBP3 overexpression in brain-seeking cells. Transient and stable knockdown of IGF-IR results in a downregulation of IGF-IR downstream signaling through phospho-AKT, as well as decreased in vitro migration and invasion of MDA- MB-231Br brain-seeking cells. Using an in vivo experimental brain metastasis model, we show that IGF-IR ablation attenuates the establishment of brain metastases and prolongs survival. Finally, we demonstrate that the malignancy of brain-seeking cells is attenuated by pharmacological inhibition with picropodophyllin, an IGF-IR-specific tyrosine kinase inhibitor. Together, our data suggest that the IGF-IR is an important mediator of brain metastasis and its ablation delays the onset of brain metastases in our model system.

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A major goal of chemotherapy is to selectively kill cancer cells while minimizing toxicity to normal cells. Identifying biological differences between cancer and normal cells is essential in designing new strategies to improve therapeutic selectivity. Superoxide dismutases (SOD) are crucial antioxidant enzymes required for the elimination of superoxide (O2·− ), a free radical produced during normal cellular metabolism. Previous studies in our laboratory demonstrated that 2-methoxyestradiol (2-ME), an estradiol derivative, inhibits the function of SOD and selectively kills human leukemia cells without exhibiting significant cytotoxicity in normal lymphocytes. The present work was initiated to examine the biochemical basis for the selective anticancer activity of 2-ME. Investigations using two-parameter flow cytometric analyses and ROS scavengers established that O2·− is a primary and essential mediator of 2-ME-induced apoptosis in cancer cells. In addition, experiments using SOD overexpression vectors and SOD knockout cells found that SOD is a critical target of 2-ME. Importantly, the administration of 2-ME resulted in the selective accumulation of O 2·− and apoptosis in leukemia and ovarian cancer cells. The preferential activity of 2-ME was found to be due to increased intrinsic oxidative stress in these cancer cells versus their normal counterparts. This intrinsic oxidative stress was associated with the upregulation of the antioxidant enzymes SOD and catalase as a mechanism to cope with the increase in ROS. Furthermore, oxygen consumption experiments revealed that normal lymphocytes decrease their respiration rate in response to 2-ME-induced oxidative stress, while human leukemia cells seem to lack this regulatory mechanism. This leads to an uncontrolled production of O2·−, severe accumulation of ROS, and ultimately ROS-mediated apoptosis in leukemia cells treated with 2-ME. The biochemical differences between cancer and normal cells identified here provide a basis for the development of drug combination strategies using 2-ME with other ROS-generating agents to enhance anticancer activity. The effectiveness of such a combination strategy in killing cancer cells was demonstrated by the use of 2-ME with agents/modalities such as ionizing radiation and doxorubicin. Collectively, the data presented here strongly suggests that 2-ME may have important clinical implications for the selective killing of cancer cells. ^

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Cognitive linguistics have conscientiously pointed out the pervasiveness of conceptual mappings, particularly as conceptual blending and integration, that underlie language and that are unconsciously used in everyday speech (Fauconnier 1997, Fauconnier & Turner 2002; Rohrer 2007; Grady, Oakley & Coulson 1999). Moreover, as a further development of this work, there is a growing interest in research devoted to the conceptual mappings that make up specialized technical disciplines. Lakoff & Núñez 2000, for example, have produced a major breakthrough on the understanding of concepts in mathematics, through conceptual metaphor and as a result not of purely abstract concepts but rather of embodiment. On the engineering and architecture front, analyses on the use of metaphor, blending and categorization in English and Spanish have likewise appeared in recent times (Úbeda 2001, Roldán 1999, Caballero 2003a, 2003b, Roldán & Ubeda 2006, Roldán & Protasenia 2007). The present paper seeks to show a number of significant conceptual mappings underlying the language of architecture and civil engineering that seem to shape the way engineers and architects communicate. In order to work with a significant segment of linguistic expressions in this field, a corpus taken from a widely used technical Spanish engineering journal article was collected and analysed. The examination of the data obtained indicates that many tokens make a direct reference to therapeutic conceptual mappings, highlighting medical domains such as diagnosing,treating and curing. Hence, the paper illustrates how this notion is instantiated by the corresponding bodily conceptual integration. In addition, we wish to underline the function of visual metaphors in the world of modern architecture by evoking parts of human or animal anatomy, and how this is visibly noticeable in contemporary buildings and public works structures.

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La diabetes mellitus es el conjunto de alteraciones provocadas por un defecto en la cantidad de insulina secretada o por un aprovechamiento deficiente de la misma. Es causa directa de complicaciones a corto, medio y largo plazo que disminuyen la calidad y las expectativas de vida de las personas con diabetes. La diabetes mellitus es en la actualidad uno de los problemas más importantes de salud. Ha triplicado su prevalencia en los últimos 20 anos y para el año 2025 se espera que existan casi 300 millones de personas con diabetes. Este aumento de la prevalencia junto con la morbi-mortalidad asociada a sus complicaciones micro y macro-vasculares convierten la diabetes en una carga para los sistemas sanitarios, sus recursos económicos y sus profesionales, haciendo de la enfermedad un problema individual y de salud pública de enormes proporciones. De momento no existe cura a esta enfermedad, de modo que el objetivo terapéutico del tratamiento de la diabetes se centra en la normalización de la glucemia intentando minimizar los eventos de hiper e hipoglucemia y evitando la aparición o al menos retrasando la evolución de las complicaciones vasculares, que constituyen la principal causa de morbi-mortalidad de las personas con diabetes. Un adecuado control diabetológico implica un tratamiento individualizado que considere multitud de factores para cada paciente (edad, actividad física, hábitos alimentarios, presencia de complicaciones asociadas o no a la diabetes, factores culturales, etc.). Sin embargo, a corto plazo, las dos variables más influyentes que el paciente ha de manejar para intervenir sobre su nivel glucémico son la insulina administrada y la dieta. Ambas presentan un retardo entre el momento de su aplicación y el comienzo de su acción, asociado a la absorción de los mismos. Por este motivo la capacidad de predecir la evolución del perfil glucémico en un futuro cercano, ayudara al paciente a tomar las decisiones adecuadas para mantener un buen control de su enfermedad y evitar situaciones de riesgo. Este es el objetivo de la predicción en diabetes: adelantar la evolución del perfil glucémico en un futuro cercano para ayudar al paciente a adaptar su estilo de vida y sus acciones correctoras, con el propósito de que sus niveles de glucemia se aproximen a los de una persona sana, evitando así los síntomas y complicaciones de un mal control. La aparición reciente de los sistemas de monitorización continua de glucosa ha proporcionado nuevas alternativas. La disponibilidad de un registro exhaustivo de las variaciones del perfil glucémico, con un periodo de muestreo de entre uno y cinco minutos, ha favorecido el planteamiento de nuevos modelos que tratan de predecir la glucemia utilizando tan solo las medidas anteriores de glucemia o al menos reduciendo significativamente la información de entrada a los algoritmos. El hecho de requerir menor intervención por parte del paciente, abre nuevas posibilidades de aplicación de los predictores de glucemia, haciéndose viable su uso en tiempo real, como sistemas de ayuda a la decisión, como detectores de situaciones de riesgo o integrados en algoritmos automáticos de control. En esta tesis doctoral se proponen diferentes algoritmos de predicción de glucemia para pacientes con diabetes, basados en la información registrada por un sistema de monitorización continua de glucosa así como incorporando la información de la insulina administrada y la ingesta de carbohidratos. Los algoritmos propuestos han sido evaluados en simulación y utilizando datos de pacientes registrados en diferentes estudios clínicos. Para ello se ha desarrollado una amplia metodología, que trata de caracterizar las prestaciones de los modelos de predicción desde todos los puntos de vista: precisión, retardo, ruido y capacidad de detección de situaciones de riesgo. Se han desarrollado las herramientas de simulación necesarias y se han analizado y preparado las bases de datos de pacientes. También se ha probado uno de los algoritmos propuestos para comprobar la validez de la predicción en tiempo real en un escenario clínico. Se han desarrollado las herramientas que han permitido llevar a cabo el protocolo experimental definido, en el que el paciente consulta la predicción bajo demanda y tiene el control sobre las variables metabólicas. Este experimento ha permitido valorar el impacto sobre el control glucémico del uso de la predicción de glucosa. ABSTRACT Diabetes mellitus is the set of alterations caused by a defect in the amount of secreted insulin or a suboptimal use of insulin. It causes complications in the short, medium and long term that affect the quality of life and reduce the life expectancy of people with diabetes. Diabetes mellitus is currently one of the most important health problems. Prevalence has tripled in the past 20 years and estimations point out that it will affect almost 300 million people by 2025. Due to this increased prevalence, as well as to morbidity and mortality associated with micro- and macrovascular complications, diabetes has become a burden on health systems, their financial resources and their professionals, thus making the disease a major individual and a public health problem. There is currently no cure for this disease, so that the therapeutic goal of diabetes treatment focuses on normalizing blood glucose events. The aim is to minimize hyper- and hypoglycemia and to avoid, or at least to delay, the appearance and development of vascular complications, which are the main cause of morbidity and mortality among people with diabetes. A suitable, individualized and controlled treatment for diabetes involves many factors that need to be considered for each patient: age, physical activity, eating habits, presence of complications related or unrelated to diabetes, cultural factors, etc. However, in the short term, the two most influential variables that the patient has available in order to manage his/her glycemic levels are administered insulin doses and diet. Both suffer from a delay between their time of application and the onset of the action associated with their absorption. Therefore, the ability to predict the evolution of the glycemic profile in the near future could help the patient to make appropriate decisions on how to maintain good control of his/her disease and to avoid risky situations. Hence, the main goal of glucose prediction in diabetes consists of advancing the evolution of glycemic profiles in the near future. This would assist the patient in adapting his/her lifestyle and in taking corrective actions in a way that blood glucose levels approach those of a healthy person, consequently avoiding the symptoms and complications of a poor glucose control. The recent emergence of continuous glucose monitoring systems has provided new alternatives in this field. The availability of continuous records of changes in glycemic profiles (with a sampling period of one or five minutes) has enabled the design of new models which seek to predict blood glucose by using automatically read glucose measurements only (or at least, reducing significantly the data input manually to the algorithms). By requiring less intervention by the patient, new possibilities are open for the application of glucose predictors, making its use feasible in real-time applications, such as: decision support systems, hypo- and hyperglycemia detectors, integration into automated control algorithms, etc. In this thesis, different glucose prediction algorithms are proposed for patients with diabetes. These are based on information recorded by a continuous glucose monitoring system and incorporate information of the administered insulin and carbohydrate intakes. The proposed algorithms have been evaluated in-silico and using patients’ data recorded in different clinical trials. A complete methodology has been developed to characterize the performance of predictive models from all points of view: accuracy, delay, noise and ability to detect hypo- and hyperglycemia. In addition, simulation tools and patient databases have been deployed. One of the proposed algorithms has additionally been evaluated in terms of real-time prediction performance in a clinical scenario in which the patient checked his/her glucose predictions on demand and he/she had control on his/her metabolic variables. This has allowed assessing the impact of using glucose prediction on glycemic control. The tools to carry out the defined experimental protocols were also developed in this thesis.

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Nonobese diabetic (NOD) mice develop insulin-dependent diabetes mellitus due to autoimmune T lymphocyte-mediated destruction of pancreatic β cells. Although both major histocompatibility complex class I-restricted CD8+ and class II-restricted CD4+ T cell subsets are required, the specific role each subset plays in the pathogenic process is still unclear. Here we show that class I-dependent T cells are required for all but the terminal stages of autoimmune diabetes development. To characterize the diabetogenic CD8+ T cells responsible, we isolated and propagated in vitro CD8+ T cells from the earliest insulitic lesions of NOD mice. They were cytotoxic to NOD islet cells, restricted to H-2Kd, and showed a diverse T cell receptor β chain repertoire. In contrast, their α chain repertoire was more restricted, with a recurrent amino acid sequence motif in the complementarity-determining region 3 loop and a prevalence of Vα17 family members frequently joined to the Jα42 gene segment. These results suggest that a number of the CD8+ T cells participating in the initial phase of autoimmune β cell destruction recognize a common structural component of Kd/peptide complexes on pancreatic β cells, possibly a single peptide.

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Impaired insulin secretion is a characteristic of non-insulin-dependent diabetes mellitus (NIDDM). One possible therapeutic agent for NIDDM is the insulinotropic hormone glucagon-like peptide 1 (GLP-1). GLP-1 stimulates insulin secretion through several mechanisms including activation of protein kinase A (PKA). We now demonstrate that the subcellular targeting of PKA through association with A-kinase-anchoring proteins (AKAPs) facilitates GLP-1-mediated insulin secretion. Disruption of PKA anchoring by the introduction of anchoring inhibitor peptides or expression of soluble AKAP fragments blocks GLP-1 action in primary islets and cAMP-responsive insulin secretion in clonal beta cells (RINm5F). Displacement of PKA also prevented cAMP-mediated elevation of intracellular calcium suggesting that localized PKA phosphorylation events augment calcium flux.